Many smartphone applications or services require position information, e.g., location based services including mobile advertisement, mobile social network and etc.
Hence, in today's modern mobile devices, two positioning functions are usually provided: Global Positioning System (GPS) function and network based positioning function, such as cell-ID or WiFi Access Point (AP) based positioning functions. WiFi is a technology that allows electronic devices to exchange data or connect to Internet wirelessly using radio waves.
A GPS receiver calculates its position by precisely determining timing of signals sent by a set of GPS satellites that transmits those signals. The GPS receiver, when comprised in a mobile device, is usually accurate to within 10-20 meters on an average.
Some network based positioning functions use cell identification (Cell-ID) of a cellular network and a Media Access Control (MAC) address, e.g. according to an 802.11 AP MAC address, to estimate a position of a mobile device. A network based positioning function may use a location of a base station, comprised in a cellular network, as an estimate of the position of the mobile device. It shall be noted that the position of the base station is already known and stored in a database that may be managed by the cellular network. The accuracy achieved with this network based positioning function relies on the cell size which can be up to several km in the cellular network. Other network based positioning functions, such as WiFi positioning, applies a similar approach as the network based positioning function, which uses cell ID as described above. Instead of the positions of the base stations of the cellular network, geographical information about positions of WiFi APs are kept in a database which can be looked up for making an estimation of a position for a mobile device that is connected to an WiFi AP.
Large scale statistical studies, such as Gonzalez, M. C., Hidalgo, C. A., Barabasi, A. L., “Understanding individual human mobility patterns”. Nature 453(7196), 2008 and Song, C., Qu, Z., Blumm, N., Barabsi, A. L.: “Limits of predictability in human mobility”, Science 327(5968), 2010, have shown that most people have regular daily routines of moving and traveling. This provides an opportunity for predicting and estimating a person's movements, i.e. a mobile device that the person carries, given that this person has been observed for some time.
Although several positioning systems are already available as mentioned above, they have some inherent limitations. Network based positioning functions are highly energy efficient, but are often prone to errors as high as several kilometers. Disadvantageously, an accuracy of several kilometers may be insufficient for some location based applications that may require more accurate estimation of the position of the mobile device.
The GPS function mentioned above provides good accuracy, but it is also well known that GPS receivers are very power-consuming. Therefore, keeping the GPS receiver activated continuously would normally drain a battery of the mobile device quickly, even in the absence of any other activities, such as cellular network transmissions. This is an obstacle towards all-day usage of location based services in mobile devices.
There are already some existing efforts that attempt to reduce the energy consumption for positioning functions in mobile devices. In EP2464182 A2, a method for navigation based on a Cell-ID aided positioning system is disclosed. A mobile user's current position is determined based stored route information. The route information includes recorded sequences of Cell-IDs and GPS information. A length of the recorded sequence of cell-IDs is fixed, for example 10. Then, a current sequence of cell-IDs is identified. A length of the current sequence of cell-IDs is also fixed, but shorter than the recorded sequences of cell-ID, for example 5. Then, the current sequence of cell-IDs is matched against the recorded sequence of Cell-IDs. If there is a match, temporal interpolation and the GPS information is used to estimate the current position.
A problem with known positioning methods based on prediction is that accuracy is not high enough for some applications.